1. Field of the Invention
The present invention relates generally to automated tool mark analysis and, more particularly, to the automated acquisition and comparison of tool mark data using three-dimensional information.
2. Brief Discussion of the Related Art
Objects that are acted or operated on by tools are normally left with tool marks as a result of being acted or operated on by the tools. Many types of commonly used mechanical tools, such as screw drivers, pliers, bolt cutters, crimping tools, hammers and other mechanical tools, impart tool marks to the objects they are used on. Tool marks generally comprise regions where the surfaces of the objects have been deformed or altered because microscopic imperfections on the working surface or surfaces of a particular tool are transferred to the surface of the object on which the tool is used, creating depth or elevational variances in the surfaces of the objects. An individual tool mark may present many depth or elevational variances, and these variances are often microscopic so as to be indetectable with the naked eye. Different types of tools will ordinarily create different types of tool marks in accordance with the structure of the tool and the manner in which the tool operates to apply force or pressure to the object. Tool marks that predominantly present striations may be considered striated tool marks, and tools that impart striated tool marks may be referred to as striation-creating tools. Tool marks that predominantly present impressions may be considered impressed tool marks, and tools that impart impressed tool marks may be referred to as impression-creating tools. Some tools may be both striation-creating and impression-creating tools. Slotted screw drivers and tongue and groove pliers are examples of tools that create striated tool marks on objects on which the tools are operatively utilized. Crimping tools, bolt cutters and hammers are examples of tools that create impressed tool marks on objects on which the tools are operatively utilized. Tongue and groove pliers are representative of tools that can create impressed tool marks and striated tool marks (along two possible axes, parallel and perpendicular to the plier jaws) on objects on which the tools are operatively utilized.
Forensic examination of tool marks is normally performed by a tool marks examiner, who is responsible for determining whether a suspect tool created an evidence tool mark. In practice, the tool marks examiner typically creates test tool marks using the suspect tool, and then compares microscopic surface features of the test tool marks with microscopic surface features of the evidence tool mark. Currently these tool mark-to-tool mark comparisons are made manually by the tool marks examiner visually inspecting pairs of tool marks under a comparison microscope, making forensic tool mark examination a very time consuming process. In reaching a conclusion, the tool marks examiner relies on his or her training and judgement, thusly requiring for credibility a high level of training and skill on the part of the tool marks examiner. Even if certain of a particular conclusion, however, the tool marks examiner is generally unable to quantify his or her level of certainty or the probability of making an erroneous conclusion. The foregoing limitations of current tool mark evaluation are particularly disadvantageous in view of the raised expectations for quantitative precision in forensic analysis resulting from the development of DNA identification techniques and the high level of accuracy achievable in the establishment of error rates associated with DNA identification. In addition, recent Supreme Court decisions have established a trend toward requiring objective validity for forensic and scientific testimony and evidence.
Automated comparison and analysis systems have been proposed for forensic identification, and the majority of these rely on two dimensional (2D) representations of the three dimensional (3D) surface features of objects or specimens. The 2D representations are derived from 2D data acquisition which is fundamentally an indirect measurement of the 3D surface features. In 2D data acquisition, a source of light is directed at the specimen's surface, and a camera records the light as it is reflected by the specimen's surface. The 2D data acquisition process is based on the fact that the light reflected by the specimen's surface is a function of its surface features. For this 2D acquisition methodology to be effective, the incident light angle and the camera view angle cannot be the same with respect to the specimen's surface and, in actuality, must be significantly different in order to obtain a pattern of dark-and-bright reflections of the specimen's surface.
One problem of 2D data acquisition is that the transformation relating light incident on the specimen's surface and light reflected by the specimen's surface depends not only on the surface features but also on numerous independent parameters including the incident light angle, the camera angle, variations in the reflectivity of the specimen's surface, light intensity and accurate specimen orientation. Consequently, the acquired 2D data is also dependent on these parameters. Existing 2D-based analysis and comparison systems ordinarily do not compensate for the effects of these parameters on the acquired 2D data. Another problem of 2D data acquisition relates to the phenomenon of “shadowing” resulting from smaller surface features being “shadowed” by larger surface features for a given incident light angle. Arbitrarily small changes in the incident light angle may determine whether certain surface features are detected or not, and a similar problem applies to the angle of view of the camera. In mathematical terms, the transformation between the incident light and the reflected light is discontinuous with respect to the incident light angle (and the angle of view of the camera), such that there may be regions of the specimen's surface where the acquired data does not accurately reflect the surface features. Some of the benefits of 2D data relate to the relatively faster speeds with which 2D data can be acquired, as opposed to 3D data, and to the familiarity of tool marks examiners with 2D representations of a specimen's surface.
In contrast to 2D data acquisition, 3D data acquisition is for all practical purposes a direct measurement. Data acquired using a 3D-based data acquisition methodology is in general more robust than that attainable with existing 2D-based automated microscopic examination systems. The richness of a 3D characterization of the surface of an object surpasses that of a 2D characterization. Furthermore, 3D-based data acquisition methodologies generally avoid arbitrary large errors in the measurement of surface features in response to small variations in the incident light angle. U.S. Pat. No. 6,785,634 to Bachrach et al and No. 6,505,140 to Bachrach are representative of 3D-based automated systems and methods in the area of ballistics analysis.